This post was a brief introduction to the history of mainstream cognitive science and has some background information on the notions of ‘mental representation’ and the computational metaphor, which are going to be looked at critically in this post.
The Computational Metaphor
Anthony Chemero, author of Radical Embodied Cognitive Science (2009) expresses in his opening chapter that a description or metaphor in science is acceptable, only as long as it furthers our understanding of a problem.
Sticking points arise, however, when a metaphor become so entrenched in the intellectual community that it becomes the object of study itself. Within cognitive science, the computational metaphor has successfully embedded and reinforced itself by rewriting the central aim of Psychology. Cognitive science has become preoccupied with elucidating the nature of representations (supposedly functionally invoked entities), rather than examining critically whether the metaphor is fit for purpose. Metaphors not only constrain our understanding of the behaviour under scrutiny, but also constrain the questions that are being asked.
This is a trivial issue if, like Fodor (1987), we believe that a representational language of thought is theoretically non-negotiable when explaining human perceptual and cognitive capabilities. While Fodor (2003) himself admits that this approach is currently without a psychosemantic theory of content (which I’ll get to later), the lack of urgency to find such an account is implicitly vindicated by the lazy mantra of ‘what else could it be?’. Traditional cognitivism will eventually have to bear this burden of explanation in the face of any viable alternative to studying human behaviour.
One such alternative is Radical Embodied Cognitive Science which studies behaviour from a Systems Theory perspective. This post will look at what such a view entails and having considered this alternative account of complex behaviour, the post will finally consider the metaphysical consequences of assuming that we have contentful mental representations which are computed over and also the feasibility of “information transmission”. Hopefully this will go some way towards questioning whether representationalism warrants its status as the default theoretical stance in cognitive science.
The “radical” of “Radical Embodied Cognitive Science” refers to its anti-representationalist stance and it seeks instead to explain behaviours in terms of the system of brain, body and environment interaction.
Van Gelder’s (1995) seminal paper “What Might Cognition Be If Not Computation?” makes a useful example of the Steam Governor, which was a device designed by the mechanical engineer James Watt to regulate steam engines. The aim was to maintain the speed of the driving flywheel smoothly in the face of large fluctuations in steam pressure and workload. This could be controlled via the turn of the throttle, which was the gateway for the steam.
From the perspective of a computational designer, we might regulate the speed of the flywheel by measuring the speed, comparing it to the desired speed, calculating how to adjust the throttle that restricts/facilitates steam flow and then implementing the change. This appears to be a task which perfectly illustrates the need to posit some sort of information processing mechanism, in which information on current and desired speed (content) is transmitted, interpreted and computed over.
However, the actual Governor does not perform any of these complex calculations at all, but still regulates the engine – and it does so incredibly well.
In the governor, a spindle is geared to the flywheel, whose rotation speed directly depends on the speed of the flywheel. Attached by hinges to the spindle are two arms, each with a metal ball attached at the end. These in turn are connected to the throttle itself. The movement of the spindle creates a centrifugal force, resulting in the balls being driven up and out. This means that when speed increases, the rising balls immediately begin restricting the flow of steam (and vice versa). The solution to the problem is immediate, continuous and smooth; the system is robust to large changes in pressure and load and maintains the desired speed effectively.
The Nature of Representation
The Watts governor is a dynamical system in which the arm angle of the system covaries with the speed of the flywheel. This could conceivably be called the system’s “representation” of speed; however, it is misleading to call this a “representation”. The system is not taking a measure of speed and performing a computation on it. In fact, there are no identifiable sub-components which perform discrete operations, whereas the computational solution clearly has such identifiable modules. The Governor does not have a schedule of rules to follow and its task is not one of translation in any meaningful sense of the word. Its activity is continuous and there is no point in time at which any part of the system is not influencing the behaviour of all other parts.
Van Gelder raises the point that the correlative relationship between arm angle and flywheel speed in fact breaks down in the system when outside of an equilibrium state, meaning that the supposed representational relationship (specified as correlation) is not even an enduring one1. However, when described within the framework of dynamical systems, mathematical description of the coupling of the parts adequately characterises the relationship between the system’s components over time in its entirety. A representational narrative not only adds nothing, but encourages us to ask misleading questions, such as how the elements ‘communicate’, how information is ‘processed’ or how a proposed ‘algorithm’ might be implemented.
While this has laid out that there do in fact exist alternative approaches to studying behaviour, it is also worth looking at traditional computationalism’s conceptual commitments and viability.
The Hard Problem of Content
Hutto and Myin (2013) define the classic representationalism stance as CIC (Cognition necessarily Involves Content) and characterise its biggest credibility hurdle as The Hard Problem of Content. This challenge holds for any theory which aims to characterise cognition within the bounds of explanatory naturalism while maintaining a CIC stance that cognition is about manipulating contentful representations.
Problems arise when attempting to explain how information maintains its integrity through transmission in different physical mediums. Invariably, attempts to ground representations in the physical world lead to fuzzy distinctions between representational vehicles (“information carriers” which are potentially amenable to physical description) and their contents. If our cognitive architecture is specialised to deal with the physical vehicles that hold the content, then what or who is the attached content meaningful for?
While covariance relations could be sufficient to constitute information, Hutto and Myin (2013) claim that this is insufficiently constrained to account for meaningful content, mirroring van Gelder’s concerns that representation-as-correlation opens the term “representation” up to trivialisation. Covariance does not constitute a state carrying information about something else without an external interpretive process imposed on it (e.g. using the number of tree rings to derive the age of the tree). In order for a state to be contentful, it must have conditions of satisfaction. Covariance is not a semantic relationship, as it is not propositional about the truth of states in the world. While organisms might respond to natural signs, this does not necessarily entail that they respond to them as stand-ins for something else.
RECS does not deny that organisms are informationally sensitive (Hutton & Myin, 2013) in that they “exploit correspondences in their environments to adaptively guide their environments” (p. 82). However, this is fundamentally distinct from claiming that information is transmitted as semantic content and presupposing some form of internal language to support the required interpretive process.
For those interested in reading about these problems in detail, their book ‘Radicalising Enactivism’ goes on to discuss potential CIC rebuttals and consequent revisions of the notion of ‘representation’ and ‘content’. This lays out the inevitable dilution of concepts that occurs during this redefining process. These terms appear to be rendered empirically implausible at worst and, at best, explanatorily irrelevant.
While this post has served to introduce a systems approach as a potential alternative to computationalism, I will later discuss in more detail a particular theoretical approach which characterises organisms as dynamical systems coupled with their environment through information. This approach does not rely on the concepts of representation or information transmission and therefore, unlike cognitivist theories, avoids the troublesome and persistent demand to provide a coherent theory of content.
1There is a small but significant differential between arm angle and speed when the flywheel slows quickly. Whilst the flywheel can slow almost instantly, the rate at which the arms can fall is dictated by gravity and it is during this fall that their angle cannot be correlated to the speed of the flywheel.
Chemero, A. (2009). Radical embodied cognitive science. MIT Press.
Fodor, J. (1987). Psychosemantics. MA: MIT Press.
Fodor, J. (2003). Hume Variations. Oxford: Oxford University Press.
Hutto, D. D. & Myin, E. (2013) Radicalising enactivism: Basic minds without content. Cambridge, MA, MIT Press.
Van Gelder, T. (1995). What might cognition be, if not computation?. The Journal of Philosophy, 92(7), 345-381.